Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	1350
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	1
Duplicate rows (%)	0.1%
Total size in memory	147.8 KiB
Average record size in memory	112.1 B

Variable types

Numeric	9
Categorical	5

Alerts

Dataset has 1 (0.1%) duplicate rows	Duplicates
`Overall Qual` is highly correlated with `Gr Liv Area` and 7 other fields	High correlation
`Gr Liv Area` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Garage Cars` is highly correlated with `Overall Qual` and 6 other fields	High correlation
`Garage Area` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Total Bsmt SF` is highly correlated with `1st Flr SF` and 1 other fields	High correlation
`1st Flr SF` is highly correlated with `Total Bsmt SF` and 1 other fields	High correlation
`Full Bath` is highly correlated with `Overall Qual` and 5 other fields	High correlation
`Year Built` is highly correlated with `Overall Qual` and 6 other fields	High correlation
`Year Remod/Add` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Garage Yr Blt` is highly correlated with `Overall Qual` and 6 other fields	High correlation
`target` is highly correlated with `Overall Qual` and 9 other fields	High correlation
`Overall Qual` is highly correlated with `Gr Liv Area` and 8 other fields	High correlation
`Gr Liv Area` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Garage Cars` is highly correlated with `Overall Qual` and 6 other fields	High correlation
`Garage Area` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Total Bsmt SF` is highly correlated with `Overall Qual` and 2 other fields	High correlation
`1st Flr SF` is highly correlated with `Gr Liv Area` and 2 other fields	High correlation
`Full Bath` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Year Built` is highly correlated with `Overall Qual` and 5 other fields	High correlation
`Year Remod/Add` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Garage Yr Blt` is highly correlated with `Overall Qual` and 5 other fields	High correlation
`target` is highly correlated with `Overall Qual` and 9 other fields	High correlation
`Overall Qual` is highly correlated with `Garage Cars` and 3 other fields	High correlation
`Gr Liv Area` is highly correlated with `Full Bath` and 1 other fields	High correlation
`Garage Cars` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Garage Area` is highly correlated with `Garage Cars`	High correlation
`Total Bsmt SF` is highly correlated with `1st Flr SF`	High correlation
`1st Flr SF` is highly correlated with `Total Bsmt SF`	High correlation
`Full Bath` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Year Built` is highly correlated with `Overall Qual` and 2 other fields	High correlation
`Year Remod/Add` is highly correlated with `Year Built` and 1 other fields	High correlation
`Garage Yr Blt` is highly correlated with `Garage Cars` and 2 other fields	High correlation
`target` is highly correlated with `Overall Qual` and 3 other fields	High correlation
`Exter Qual` is highly correlated with `Kitchen Qual`	High correlation
`Kitchen Qual` is highly correlated with `Exter Qual`	High correlation
`Overall Qual` is highly correlated with `Gr Liv Area` and 9 other fields	High correlation
`Gr Liv Area` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Exter Qual` is highly correlated with `Overall Qual` and 5 other fields	High correlation
`Garage Cars` is highly correlated with `Overall Qual` and 8 other fields	High correlation
`Garage Area` is highly correlated with `Overall Qual` and 8 other fields	High correlation
`Kitchen Qual` is highly correlated with `Overall Qual` and 4 other fields	High correlation
`Total Bsmt SF` is highly correlated with `Gr Liv Area` and 5 other fields	High correlation
`1st Flr SF` is highly correlated with `Gr Liv Area` and 4 other fields	High correlation
`Bsmt Qual` is highly correlated with `Overall Qual` and 9 other fields	High correlation
`Full Bath` is highly correlated with `Overall Qual` and 8 other fields	High correlation
`Year Built` is highly correlated with `Overall Qual` and 9 other fields	High correlation
`Year Remod/Add` is highly correlated with `Exter Qual` and 6 other fields	High correlation
`Garage Yr Blt` is highly correlated with `Overall Qual` and 7 other fields	High correlation
`target` is highly correlated with `Overall Qual` and 12 other fields	High correlation

Reproduction

Analysis started	2022-02-03 08:30:43.668184
Analysis finished	2022-02-03 08:31:10.901057
Duration	27.23 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

Overall Qual
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.208888889

Minimum	2
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	5
median	6
Q3	7
95-th percentile	9
Maximum	10
Range	8
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.338015008
Coefficient of variation (CV)	0.2154999118
Kurtosis	-0.07763476292
Mean	6.208888889
Median Absolute Deviation (MAD)	1
Skewness	0.345323694
Sum	8382
Variance	1.790284161
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
5	379	28.1%
6	351	26.0%
7	307	22.7%
8	156	11.6%
4	75	5.6%
9	56	4.1%
10	15	1.1%
3	8	0.6%
2	3	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	3	0.2%
3	8	0.6%
4	75	5.6%
5	379	28.1%
6	351	26.0%
7	307	22.7%
8	156	11.6%
9	56	4.1%
10	15	1.1%

Value	Count	Frequency (%)
10	15	1.1%
9	56	4.1%
8	156	11.6%
7	307	22.7%
6	351	26.0%
5	379	28.1%
4	75	5.6%
3	8	0.6%
2	3	0.2%

Gr Liv Area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	813
Distinct (%)	60.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1513.542222

Minimum	480
Maximum	4476
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	480
5-th percentile	869.8
Q1	1144
median	1445.5
Q3	1774.5
95-th percentile	2498.1
Maximum	4476
Range	3996
Interquartile range (IQR)	630.5

Descriptive statistics

Standard deviation	487.5232386
Coefficient of variation (CV)	0.3221074585
Kurtosis	1.516308644
Mean	1513.542222
Median Absolute Deviation (MAD)	313.5
Skewness	0.9803084672
Sum	2043282
Variance	237678.9081
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
864	19	1.4%
1040	12	0.9%
1092	12	0.9%
894	11	0.8%
1200	9	0.7%
1456	9	0.7%
1224	7	0.5%
960	7	0.5%
848	7	0.5%
988	7	0.5%
Other values (803)	1250	92.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
480	1	0.1%
520	1	0.1%
540	1	0.1%
572	1	0.1%
630	2	0.1%
672	2	0.1%
694	1	0.1%
747	1	0.1%
764	1	0.1%
765	1	0.1%

Value	Count	Frequency (%)
4476	1	0.1%
3627	1	0.1%
3608	1	0.1%
3194	1	0.1%
3140	1	0.1%
3082	1	0.1%
3005	1	0.1%
2978	1	0.1%
2956	1	0.1%
2945	1	0.1%

Exter Qual
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	10.7 KiB

TA	808
Gd	485
Ex	49
Fa	8

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Ex
2nd row	Gd
3rd row	TA
4th row	TA
5th row	Gd

Common Values

Value	Count	Frequency (%)
TA	808	59.9%
Gd	485	35.9%
Ex	49	3.6%
Fa	8	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
ta	808	59.9%
gd	485	35.9%
ex	49	3.6%
fa	8	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Garage Cars
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	10.7 KiB

2	794
1	372
3	172
4	11
5	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	3
2nd row	2
3rd row	1
4th row	2
5th row	3

Common Values

Value	Count	Frequency (%)
2	794	58.8%
1	372	27.6%
3	172	12.7%
4	11	0.8%
5	1	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	794	58.8%
1	372	27.6%
3	172	12.7%
4	11	0.8%
5	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Garage Area
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	454
Distinct (%)	33.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	502.0148148

Minimum	100
Maximum	1488
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	100
5-th percentile	240
Q1	368
median	484
Q3	588
95-th percentile	865.55
Maximum	1488
Range	1388
Interquartile range (IQR)	220

Descriptive statistics

Standard deviation	191.3899564
Coefficient of variation (CV)	0.3812436422
Kurtosis	1.522404855
Mean	502.0148148
Median Absolute Deviation (MAD)	110.5
Skewness	0.8864540664
Sum	677720
Variance	36630.11542
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
440	47	3.5%
576	42	3.1%
240	37	2.7%
480	36	2.7%
484	35	2.6%
528	32	2.4%
400	28	2.1%
264	27	2.0%
288	24	1.8%
308	19	1.4%
Other values (444)	1023	75.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100	1	0.1%
160	1	0.1%
162	1	0.1%
164	1	0.1%
180	9	0.7%
184	1	0.1%
186	1	0.1%
195	2	0.1%
200	6	0.4%
205	2	0.1%

Value	Count	Frequency (%)
1488	1	0.1%
1390	1	0.1%
1356	1	0.1%
1348	1	0.1%
1314	1	0.1%
1231	1	0.1%
1220	1	0.1%
1184	1	0.1%
1138	1	0.1%
1110	1	0.1%

Kitchen Qual
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	10.7 KiB

TA	660
Gd	560
Ex	107
Fa	23

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Ex
2nd row	Gd
3rd row	TA
4th row	Gd
5th row	Gd

Common Values

Value	Count	Frequency (%)
TA	660	48.9%
Gd	560	41.5%
Ex	107	7.9%
Fa	23	1.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
ta	660	48.9%
gd	560	41.5%
ex	107	7.9%
fa	23	1.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Total Bsmt SF
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	709
Distinct (%)	52.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1082.644444

Minimum	105
Maximum	2660
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	105
5-th percentile	548.35
Q1	816
median	1009
Q3	1309.5
95-th percentile	1807.7
Maximum	2660
Range	2555
Interquartile range (IQR)	493.5

Descriptive statistics

Standard deviation	384.0677133
Coefficient of variation (CV)	0.3547496274
Kurtosis	0.60547131
Mean	1082.644444
Median Absolute Deviation (MAD)	229.5
Skewness	0.7442916706
Sum	1461570
Variance	147508.0084
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
864	37	2.7%
768	15	1.1%
1040	15	1.1%
672	14	1.0%
1008	13	1.0%
912	11	0.8%
894	11	0.8%
720	10	0.7%
816	10	0.7%
960	9	0.7%
Other values (699)	1205	89.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
105	1	0.1%
160	1	0.1%
190	1	0.1%
216	1	0.1%
240	1	0.1%
264	1	0.1%
297	1	0.1%
346	1	0.1%
356	1	0.1%
384	9	0.7%

Value	Count	Frequency (%)
2660	1	0.1%
2535	1	0.1%
2524	1	0.1%
2461	1	0.1%
2458	1	0.1%
2452	1	0.1%
2396	1	0.1%
2392	1	0.1%
2271	1	0.1%
2220	1	0.1%

1st Flr SF
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	736
Distinct (%)	54.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1167.474074

Minimum	480
Maximum	2898
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	480
5-th percentile	672
Q1	886.25
median	1092.5
Q3	1396.5
95-th percentile	1846.2
Maximum	2898
Range	2418
Interquartile range (IQR)	510.25

Descriptive statistics

Standard deviation	375.061407
Coefficient of variation (CV)	0.3212588744
Kurtosis	0.7450582024
Mean	1167.474074
Median Absolute Deviation (MAD)	236.5
Skewness	0.8317876671
Sum	1576090
Variance	140671.059
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
864	20	1.5%
1040	14	1.0%
894	11	0.8%
960	11	0.8%
848	9	0.7%
990	8	0.6%
832	8	0.6%
630	7	0.5%
912	7	0.5%
672	7	0.5%
Other values (726)	1248	92.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
480	1	0.1%
483	6	0.4%
502	1	0.1%
516	1	0.1%
520	4	0.3%
525	4	0.3%
526	2	0.1%
530	3	0.2%
536	1	0.1%
540	1	0.1%

Value	Count	Frequency (%)
2898	1	0.1%
2524	1	0.1%
2522	1	0.1%
2515	1	0.1%
2497	1	0.1%
2490	1	0.1%
2470	1	0.1%
2452	1	0.1%
2422	1	0.1%
2411	1	0.1%

Bsmt Qual
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	10.7 KiB

TA	605
Gd	582
Ex	134
Fa	28
Po	1

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	Ex
2nd row	Ex
3rd row	TA
4th row	TA
5th row	Gd

Common Values

Value	Count	Frequency (%)
TA	605	44.8%
Gd	582	43.1%
Ex	134	9.9%
Fa	28	2.1%
Po	1	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
ta	605	44.8%
gd	582	43.1%
ex	134	9.9%
fa	28	2.1%
po	1	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Full Bath
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	10.7 KiB

2	703
1	612
3	27
0	6
4	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
2	703	52.1%
1	612	45.3%
3	27	2.0%
0	6	0.4%
4	2	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	703	52.1%
1	612	45.3%
3	27	2.0%
0	6	0.4%
4	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Year Built
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	105
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1972.987407

Minimum	1880
Maximum	2010
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	1880
5-th percentile	1920
Q1	1955
median	1976
Q3	2002
95-th percentile	2007
Maximum	2010
Range	130
Interquartile range (IQR)	47

Descriptive statistics

Standard deviation	29.30725737
Coefficient of variation (CV)	0.01485425465
Kurtosis	-0.3762728739
Mean	1972.987407
Median Absolute Deviation (MAD)	23
Skewness	-0.6480337442
Sum	2663533
Variance	858.9153343
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2005	71	5.3%
2006	63	4.7%
2003	48	3.6%
2007	48	3.6%
2004	48	3.6%
1977	33	2.4%
1976	27	2.0%
2008	25	1.9%
1978	24	1.8%
1968	24	1.8%
Other values (95)	939	69.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1880	3	0.2%
1882	1	0.1%
1885	2	0.1%
1890	3	0.2%
1892	1	0.1%
1893	1	0.1%
1900	10	0.7%
1908	1	0.1%
1910	17	1.3%
1912	1	0.1%

Value	Count	Frequency (%)
2010	1	0.1%
2009	14	1.0%
2008	25	1.9%
2007	48	3.6%
2006	63	4.7%
2005	71	5.3%
2004	48	3.6%
2003	48	3.6%
2002	22	1.6%
2001	19	1.4%

Year Remod/Add
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	61
Distinct (%)	4.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1985.099259

Minimum	1950
Maximum	2010
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	1950
5-th percentile	1950
Q1	1968
median	1993
Q3	2004
95-th percentile	2007
Maximum	2010
Range	60
Interquartile range (IQR)	36

Descriptive statistics

Standard deviation	20.15324351
Coefficient of variation (CV)	0.01015225985
Kurtosis	-1.236075056
Mean	1985.099259
Median Absolute Deviation (MAD)	13
Skewness	-0.5010053957
Sum	2679884
Variance	406.1532241
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1950	134	9.9%
2006	93	6.9%
2005	68	5.0%
2007	67	5.0%
2004	58	4.3%
2003	52	3.9%
2000	43	3.2%
2008	38	2.8%
2002	37	2.7%
1998	35	2.6%
Other values (51)	725	53.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1950	134	9.9%
1951	4	0.3%
1952	9	0.7%
1953	6	0.4%
1954	14	1.0%
1955	12	0.9%
1956	12	0.9%
1957	9	0.7%
1958	17	1.3%
1959	9	0.7%

Value	Count	Frequency (%)
2010	5	0.4%
2009	17	1.3%
2008	38	2.8%
2007	67	5.0%
2006	93	6.9%
2005	68	5.0%
2004	58	4.3%
2003	52	3.9%
2002	37	2.7%
2001	23	1.7%

Garage Yr Blt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	97
Distinct (%)	7.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1978.471852

Minimum	1900
Maximum	2207
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	1900
5-th percentile	1930
Q1	1961
median	1978.5
Q3	2002
95-th percentile	2007
Maximum	2207
Range	307
Interquartile range (IQR)	41

Descriptive statistics

Standard deviation	25.37727821
Coefficient of variation (CV)	0.01282670673
Kurtosis	4.149795343
Mean	1978.471852
Median Absolute Deviation (MAD)	20.5
Skewness	-0.0419405896
Sum	2670937
Variance	644.0062493
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2005	70	5.2%
2006	53	3.9%
2007	51	3.8%
2004	50	3.7%
2003	49	3.6%
1977	40	3.0%
2008	32	2.4%
1968	29	2.1%
1993	28	2.1%
2000	27	2.0%
Other values (87)	921	68.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1900	2	0.1%
1910	3	0.2%
1914	2	0.1%
1915	2	0.1%
1916	2	0.1%
1918	1	0.1%
1919	1	0.1%
1920	14	1.0%
1921	2	0.1%
1922	6	0.4%

Value	Count	Frequency (%)
2207	1	0.1%
2010	1	0.1%
2009	17	1.3%
2008	32	2.4%
2007	51	3.8%
2006	53	3.9%
2005	70	5.2%
2004	50	3.7%
2003	49	3.6%
2002	24	1.8%

target
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	619
Distinct (%)	45.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	186406.3126

Minimum	12789
Maximum	745000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	10.7 KiB

Quantile statistics

Minimum	12789
5-th percentile	102450
Q1	135000
median	165375
Q3	217875
95-th percentile	339381.45
Maximum	745000
Range	732211
Interquartile range (IQR)	82875

Descriptive statistics

Standard deviation	78435.42476
Coefficient of variation (CV)	0.4207766554
Kurtosis	4.939592831
Mean	186406.3126
Median Absolute Deviation (MAD)	37750
Skewness	1.71758567
Sum	251648522
Variance	6152115857
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
155000	15	1.1%
140000	14	1.0%
145000	13	1.0%
135000	12	0.9%
170000	12	0.9%
144000	11	0.8%
143000	11	0.8%
105000	10	0.7%
165000	10	0.7%
110000	10	0.7%
Other values (609)	1232	91.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
12789	1	0.1%
35311	1	0.1%
50000	1	0.1%
55993	1	0.1%
58500	1	0.1%
63000	1	0.1%
64000	2	0.1%
67000	1	0.1%
68400	1	0.1%
68500	1	0.1%

Value	Count	Frequency (%)
745000	1	0.1%
625000	1	0.1%
615000	1	0.1%
591587	1	0.1%
556581	1	0.1%
535000	1	0.1%
485000	1	0.1%
475000	2	0.1%
470000	1	0.1%
468000	1	0.1%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Overall Qual	Gr Liv Area	Exter Qual	Garage Cars	Garage Area	Kitchen Qual	Total Bsmt SF	1st Flr SF	Bsmt Qual	Full Bath	Year Built	Year Remod/Add	Garage Yr Blt	target
0	10	2392	Ex	3	968	Ex	2392	2392	Ex	2	2003	2003	2003	386250
1	7	1352	Gd	2	466	Gd	1352	1352	Ex	2	2006	2007	2006	194000
2	5	900	TA	1	288	TA	864	900	TA	1	1967	1967	1967	123000
3	5	1174	TA	2	576	Gd	680	680	TA	1	1900	2006	2000	135000
4	7	1958	Gd	3	936	Gd	1026	1026	Gd	2	2005	2005	2005	250000
5	8	1968	Gd	3	680	Ex	774	774	Ex	2	2009	2010	2009	269500
6	6	1478	TA	2	442	TA	1478	1478	TA	1	1957	1957	1957	156500
7	8	2524	Gd	2	542	Gd	2524	2524	Gd	2	1981	1981	1981	278000
8	8	2649	Gd	3	746	Gd	1479	1515	Ex	2	2001	2002	2001	421250
9	8	1440	Gd	2	467	Gd	1432	1440	Ex	2	2003	2003	2003	232500

Last rows

	Overall Qual	Gr Liv Area	Exter Qual	Garage Cars	Garage Area	Kitchen Qual	Total Bsmt SF	1st Flr SF	Bsmt Qual	Full Bath	Year Built	Year Remod/Add	Garage Yr Blt	target
1340	5	925	TA	2	484	TA	925	925	TA	1	1963	1963	1990	133500
1341	4	572	TA	1	200	TA	572	572	TA	1	1925	1950	1940	75000
1342	6	2614	TA	2	624	TA	1522	1548	TA	2	1974	1997	1974	240000
1343	5	960	TA	1	392	Fa	960	960	TA	1	1959	2000	1959	131750
1344	6	865	TA	1	216	TA	660	740	TA	1	1920	1995	1920	108500
1345	6	1756	Gd	2	422	TA	872	888	Ex	2	1996	1997	1996	204000
1346	9	2748	Gd	3	850	Ex	1850	1850	Ex	2	2006	2006	2006	390000
1347	5	1214	TA	1	318	TA	1214	1214	TA	2	1967	1967	1967	143000
1348	5	894	TA	2	440	TA	864	894	Gd	1	1974	1974	1974	131000
1349	5	907	TA	1	343	TA	907	907	Gd	1	1978	1978	1978	140000

Most frequently occurring

	Overall Qual	Gr Liv Area	Exter Qual	Garage Cars	Garage Area	Kitchen Qual	Total Bsmt SF	1st Flr SF	Bsmt Qual	Full Bath	Year Built	Year Remod/Add	Garage Yr Blt	target	# duplicates
0	7	2787	TA	4	820	TA	1168	1168	Ex	4	2000	2000	2000	269500	2

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows

Duplicate rows

Most frequently occurring